Cleaning Web pages for effective Web content mining.

Web pages usually contain many noisy blocks, such as advertisements, navigation bar, copyright notice and so on. These noisy blocks can seriously affect web content mining because contents contained in noise blocks are irrelevant to the main content of the web page. Eliminating noisy blocks before performing web content mining is very important for improving mining accuracy and efficiency. A few existing approaches detect noisy blocks with exact same contents, but are weak in detecting near-duplicate blocks, such as navigation bars. In this thesis, given a collection of web pages in a web site, a new system, WebPageCleaner, which eliminates noisy blocks from these web pages so as to improve the accuracy and efficiency of web content mining, is proposed. WebPageCleaner detects both noisy blocks with exact same contents as well as those with near-duplicate contents. It is based on the observation that noisy blocks usually share common contents, and appear frequently on a given web site. WebPageCleaner consists of three modules: block extraction, block importance retrieval, and cleaned files generation. A vision-based technique is employed for extracting blocks from web pages. Blocks get their importance degree according to their block features such as block position, and level of similarity of block contents to each other. A collection of cleaned files with high importance degree are generated finally and used for web content mining. The proposed technique is evaluated using Naive Bayes text classification. Experiments show that WebPageCleaner is able to lead to a more efficient and accurate web page classification results than existing approaches.Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .L5. Source: Masters Abstracts International, Volume: 45-01, page: 0359. Thesis (M.Sc.)--University of Windsor (Canada), 2006

What Web Template Extractor Should I Use? A Benchmarking and Comparison for Five Template Extractors

"© ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in PUBLICATION, {VOL 13, ISS 2, (APR 2019)} http://doi.acm.org/10.1145/3316810"[EN] A Web template is a resource that implements the structure and format of a website, making it ready for plugging content into already formatted and prepared pages. For this reason, templates are one of the main development resources for website engineers, because they increase productivity. Templates are also useful for the final user, because they provide uniformity and a common look and feel for all webpages. However, from the point of view of crawlers and indexers, templates are an important problem, because templates usually contain irrelevant information, such as advertisements, menus, and banners. Processing and storing this information leads to a waste of resources (storage space, bandwidth, etc.). It has been measured that templates represent between 40% and 50% of data on the Web. Therefore, identifying templates is essential for indexing tasks. There exist many techniques and tools for template extraction, but, unfortunately, it is not clear at all which template extractor should a user/system use, because they have never been compared, and because they present different (complementary) features such as precision, recall, and efficiency. In this work, we compare the most advanced template extractors. We implemented and evaluated five of the most advanced template extractors in the literature. To compare all of them, we implemented a workbench, where they have been integrated and evaluated. Thanks to this workbench, we can provide a fair empirical comparison of all methods using the same benchmarks, technology, implementation language, and evaluation criteria.This work has been partially supported by the EU (FEDER) and the Spanish Ministerio de Ciencia, Innovacion y Universidades/AEI under grant TIN2016-76843-C4-1-R and by the Generalitat Valenciana under grants PROMETEO-II/2015/013 (SmartLogic) and Prometeo/2019/098 (DeepTrust).Alarte, J.; Silva, J.; Tamarit Muñoz, S. (2019). What Web Template Extractor Should I Use? A Benchmarking and Comparison for Five Template Extractors. ACM Transactions on the Web. 13(2):9:1-9:19. https://doi.org/10.1145/3316810S9:19:19132Alarte, J., Insa, D., Silva, J., & Tamarit, S. (2015). TeMex. Proceedings of the 24th International Conference on World Wide Web - WWW ’15 Companion. doi:10.1145/2740908.2742835Julián Alarte David Insa Josep Silva and Salvador Tamarit. 2016. Site-Level Web Template Extraction Based on DOM Analysis. Springer International Publishing Cham 36--49. Julián Alarte David Insa Josep Silva and Salvador Tamarit. 2016. Site-Level Web Template Extraction Based on DOM Analysis. Springer International Publishing Cham 36--49.Alassi, D., & Alhajj, R. (2013). Effectiveness of template detection on noise reduction and websites summarization. Information Sciences, 219, 41-72. doi:10.1016/j.ins.2012.07.022Bar-Yossef, Z., & Rajagopalan, S. (2002). Template detection via data mining and its applications. Proceedings of the eleventh international conference on World Wide Web - WWW ’02. doi:10.1145/511446.511522Chakrabarti, D., Kumar, R., & Punera, K. (2007). Page-level template detection via isotonic smoothing. Proceedings of the 16th international conference on World Wide Web - WWW ’07. doi:10.1145/1242572.1242582Chen, L., Ye, S., & Li, X. (2006). Template detection for large scale search engines. Proceedings of the 2006 ACM symposium on Applied computing - SAC ’06. doi:10.1145/1141277.1141534Gibson, D., Punera, K., & Tomkins, A. (2005). The volume and evolution of web page templates. Special interest tracks and posters of the 14th international conference on World Wide Web - WWW ’05. doi:10.1145/1062745.1062763Kim, C., & Shim, K. (2011). TEXT: Automatic Template Extraction from Heterogeneous Web Pages. IEEE Transactions on Knowledge and Data Engineering, 23(4), 612-626. doi:10.1109/tkde.2010.140Barbara Ann Kitchenham David Budgen and Pearl Brereton. 2015. Evidence-Based Software Engineering and Systematic Reviews. Chapman 8 Hall/CRC. Barbara Ann Kitchenham David Budgen and Pearl Brereton. 2015. Evidence-Based Software Engineering and Systematic Reviews. Chapman 8 Hall/CRC.Kołcz, A., & Yih, W. (s. f.). Site-Independent Template-Block Detection. Lecture Notes in Computer Science, 152-163. doi:10.1007/978-3-540-74976-9_17Kohlschütter, C. (2009). A densitometric analysis of web template content. Proceedings of the 18th international conference on World wide web - WWW ’09. doi:10.1145/1526709.1526909Jing Li and C. I. Ezeife. 2006. Cleaning web pages for effective web content mining. In Database and Expert Systems Applications Stéphane Bressan Josef Küng and Roland Wagner (Eds.). Springer Berlin 560--571. 10.1007/11827405_55 Jing Li and C. I. Ezeife. 2006. Cleaning web pages for effective web content mining. In Database and Expert Systems Applications Stéphane Bressan Josef Küng and Roland Wagner (Eds.). Springer Berlin 560--571. 10.1007/11827405_55Bing Liu. 2006. Web Data Mining: Exploring Hyperlinks Contents and Usage Data (Data-Centric Systems and Applications). Springer-Verlag New York Inc. Secaucus NJ. Bing Liu. 2006. Web Data Mining: Exploring Hyperlinks Contents and Usage Data (Data-Centric Systems and Applications). Springer-Verlag New York Inc. Secaucus NJ.Liu, L., Han, W., Buttler, D., Pu, C., & Tang, W. (1999). An XJML-based wrapper generator for Web information extraction. Proceedings of the 1999 ACM SIGMOD international conference on Management of data - SIGMOD ’99. doi:10.1145/304182.304570Ma, L., Goharian, N., Chowdhury, A., & Chung, M. (2003). Extracting unstructured data from template generated web documents. Proceedings of the twelfth international conference on Information and knowledge management - CIKM ’03. doi:10.1145/956863.956961Manjula, R., & Chilambuchelvan, A. (2013). Extracting templates from Web pages. 2013 International Conference on Green Computing, Communication and Conservation of Energy (ICGCE). doi:10.1109/icgce.2013.6823541Christopher D. Manning Prabhakar Raghavan and Hinrich SchÃijtze. 2008. Introduction to Information Retrieval. Cambridge University Press New York NY. Christopher D. Manning Prabhakar Raghavan and Hinrich SchÃijtze. 2008. Introduction to Information Retrieval. Cambridge University Press New York NY.Meng, X., Hu, D., & Li, C. (2003). Schema-guided wrapper maintenance for web-data extraction. Proceedings of the fifth ACM international workshop on Web information and data management - WIDM ’03. doi:10.1145/956699.956701Nguyen, D. Q., Nguyen, D. Q., Pham, S. B., & Bui, T. D. (2009). A Fast Template-Based Approach to Automatically Identify Primary Text Content of a Web Page. 2009 International Conference on Knowledge and Systems Engineering. doi:10.1109/kse.2009.39Schäfer, R. (2016). Accurate and efficient general-purpose boilerplate detection for crawled web corpora. Language Resources and Evaluation, 51(3), 873-889. doi:10.1007/s10579-016-9359-2Sivakumar, P. (2015). Effectual Web Content Mining using Noise Removal from Web Pages. Wireless Personal Communications, 84(1), 99-121. doi:10.1007/s11277-015-2596-7Song, D., Sun, F., & Liao, L. (2013). A hybrid approach for content extraction with text density and visual importance of DOM nodes. Knowledge and Information Systems, 42(1), 75-96. doi:10.1007/s10115-013-0687-xR. 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The contribution of data mining to information science

The information explosion is a serious challenge for current information institutions. On the other hand, data mining, which is the search for valuable information in large volumes of data, is one of the solutions to face this challenge. In the past several years, data mining has made a significant contribution to the field of information science. This paper examines the impact of data mining by reviewing existing applications, including personalized environments, electronic commerce, and search engines. For these three types of application, how data mining can enhance their functions is discussed. The reader of this paper is expected to get an overview of the state of the art research associated with these applications. Furthermore, we identify the limitations of current work and raise several directions for future research

WEB MINING IN E-COMMERCE

Recently, the web is becoming an important part of people’s life. The web is a very good place to run successful businesses. Selling products or services online plays an important role in the success of businesses that have a physical presence, like a reE-Commerce, Data mining, Web mining

Development of bambangan (Mangifera pajang) carbonated drink

Mangifera pajang Kostermans or bambangan is a popular fruit among Sabahan due to its health and economic values. However, the fruit is not fully commercialized since it is usually been used as traditional cuisine by local people. Thus, development of bambangan fruit into carbonated drink was conducted to produce new product concept. The objectives of this study were to conceptualize, formulate, evaluate consumer acceptance, and determine physicochemical properties and nutritional composition of the accepted product. Method used in conceptualising the product was based on questionnaire. The consumer acceptance was evaluated based on descriptive and affective tests with four product formulations tested. The physicochemical properties on carbon dioxide volume, colour, pH, total acidity, total soluble solid (TSS) and viscosity were highlighted, meanwhile nutritional composition on fat, protein, carbohydrates and energy content were determined. About 77% respondents gave positive feedback, and 69% respondents decided this product is within their budget. The formulation of 5% bambangan pulp, 70% water, 25% sugar and 0.2% citric acid was highly accepted in descriptive and affective tests with 4.4 and 6.39 mean scores, respectively. The physicochemical properties and nutritional composition of the acceptance product were in optimum value except for colour, total acidity and TSS. Overall, this study showed that the product has high potential to be commercialized as new product concept, and heritage of indigenous people can be preserved when this fruit is known regionally